Papers › STRIDE: Simple Type Recognition In Decompiled Executables
STRIDE: Simple Type Recognition In Decompiled Executables
Harrison Green, Edward J. Schwartz, Claire Le Goues, Bogdan Vasilescu
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
Decompilers are widely used by security researchers and developers to reverse engineer executable code. While modern decompilers are adept at recovering instructions, control flow, and function boundaries, some useful information from the original source code, such as variable types and names, is lost during the compilation process. Our work aims to predict these variable types and names from the remaining information. We propose STRIDE, a lightweight technique that predicts variable names and types by matching sequences of decompiler tokens to those found in training data. We evaluate it on three benchmark datasets and find that STRIDE achieves comparable performance to state-of-the-art machine learning models for both variable retyping and renaming while being much simpler and faster. We perform a detailed comparison with two recent SOTA transformer-based models in order to understand the specific factors that make our technique effective. We implemented STRIDE in fewer than 1000 lines of Python and have open-sourced it under a permissive license at https://github.com/hgarrereyn/STRIDE.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections